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      Determining the quality control frequency of an MR‐linac using risk matrix (RM) analysis


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          Quality control (QC) is performed routinely through professional guidelines. However, the recommended QC frequency may not be optimal among different institutional settings. Here we propose a novel method for determining the optimal QC frequency using risk matrix (RM) analysis.

          Methods and materials

          A newly installed Magnetic Resonance linac (MR‐linac) was chosen as the testing platform and six routine QC items were investigated. Failures of these QC items can adversely affect treatment outcome for the patient. Accordingly, each QC item with its assigned frequency forms a unique failure mode (FM). Using FM‐effect analysis (FMEA), the severity (S), occurrence (O), and detection (D) of each FM was obtained. Next, S and D based on RM was used to determine the appropriate QC frequency. Finally, the performance of new frequency for each QC item was evaluated using the metric E = O/D.


          One new QC frequency was the same as the old frequency, two new QC frequencies were less than the old ones, and three new QC frequencies were higher than the old ones. For six QC items, E values at the new frequencies were not less than their values at the old frequencies. This indicates that the risk of machine failure is reduced at the new QC frequencies.


          The application of RM analysis provides a useful tool for determining the optimal frequencies for routine linac QC. This study demonstrated that linac QC can be performed in a way that maintains high performance of the treatment machine in a radiotherapy clinic.

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          Most cited references33

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          Task Group 142 report: quality assurance of medical accelerators.

          The task group (TG) for quality assurance of medical accelerators was constituted by the American Association of Physicists in Medicine's Science Council under the direction of the Radiation Therapy Committee and the Quality Assurance and Outcome Improvement Subcommittee. The task group (TG-142) had two main charges. First to update, as needed, recommendations of Table II of the AAPM TG-40 report on quality assurance and second, to add recommendations for asymmetric jaws, multileaf collimation (MLC), and dynamic/virtual wedges. The TG accomplished the update to TG-40, specifying new test and tolerances, and has added recommendations for not only the new ancillary delivery technologies but also for imaging devices that are part of the linear accelerator. The imaging devices include x-ray imaging, photon portal imaging, and cone-beam CT. The TG report was designed to account for the types of treatments delivered with the particular machine. For example, machines that are used for radiosurgery treatments or intensity-modulated radiotherapy (IMRT) require different tests and/or tolerances. There are specific recommendations for MLC quality assurance for machines performing IMRT. The report also gives recommendations as to action levels for the physicists to implement particular actions, whether they are inspection, scheduled action, or immediate and corrective action. The report is geared to be flexible for the physicist to customize the QA program depending on clinical utility. There are specific tables according to daily, monthly, and annual reviews, along with unique tables for wedge systems, MLC, and imaging checks. The report also gives specific recommendations regarding setup of a QA program by the physicist in regards to building a QA team, establishing procedures, training of personnel, documentation, and end-to-end system checks. The tabulated items of this report have been considerably expanded as compared with the original TG-40 report and the recommended tolerances accommodate differences in the intended use of the machine functionality (non-IMRT, IMRT, and stereotactic delivery).
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            The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management.

            The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for "intensity modulated radiation therapy (IMRT)" as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy safer and more efficient.
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              Evaluation of safety in a radiation oncology setting using failure mode and effects analysis.

              Failure mode and effects analysis (FMEA) is a widely used tool for prospectively evaluating safety and reliability. We report our experiences in applying FMEA in the setting of radiation oncology. We performed an FMEA analysis for our external beam radiation therapy service, which consisted of the following tasks: (1) create a visual map of the process, (2) identify possible failure modes; assign risk probability numbers (RPN) to each failure mode based on tabulated scores for the severity, frequency of occurrence, and detectability, each on a scale of 1 to 10; and (3) identify improvements that are both feasible and effective. The RPN scores can span a range of 1 to 1000, with higher scores indicating the relative importance of a given failure mode. Our process map consisted of 269 different nodes. We identified 127 possible failure modes with RPN scores ranging from 2 to 160. Fifteen of the top-ranked failure modes were considered for process improvements, representing RPN scores of 75 and more. These specific improvement suggestions were incorporated into our practice with a review and implementation by each department team responsible for the process. The FMEA technique provides a systematic method for finding vulnerabilities in a process before they result in an error. The FMEA framework can naturally incorporate further quantification and monitoring. A general-use system for incident and near miss reporting would be useful in this regard.

                Author and article information

                J Appl Clin Med Phys
                J Appl Clin Med Phys
                Journal of Applied Clinical Medical Physics
                John Wiley and Sons Inc. (Hoboken )
                24 April 2023
                August 2023
                : 24
                : 8 ( doiID: 10.1002/acm2.v24.8 )
                : e13984
                [ 1 ] National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
                Author notes
                [*] [* ] Correspondence

                Jianrong Dai, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

                Email: dai_jianrong@ 123456cicams.ac.cn

                Author information
                © 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                : 28 February 2023
                : 08 August 2022
                : 20 March 2023
                Page count
                Figures: 4, Tables: 6, Pages: 9, Words: 5421
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 11875320
                Award ID: 11975312
                Radiation Oncology Physics
                Radiation Oncology Physics
                Custom metadata
                August 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.2 mode:remove_FC converted:04.08.2023

                failure mode and effect analysis,frequency,quality control,risk matrix


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